All level tracks Track 1 sessions are for All Levels
Track 2 sessions are Expert/Practitioner Level

Full Agenda – Toronto 2013

Conference Day 1: Wednesday, March 20, 2013

8:00-9:00am • Room: Foyer

Registration & Networking Breakfast


9:00-9:05am • Room: 713

Conference Chair Welcome Remarks

Speaker: Richard Boire, Conference Chair, Predictive Analytics World Toronto


Deloitte 9:05-9:20am • Room: 713

Diamond Sponsor Presentation
Wading Into Big Data Waters: When to Tread Lightly and When to Dive In

"Big Data" – By now, you know it's big news – perhaps bigger, even, than the name suggests. Big data refers not only to the historic influx of structured and non-structured data from non-traditional sources, but also to the big questions facing organizations wading into big data waters: How do we store, analyze and harness this data? Will it really change how we understand and respond to customers? And when should you be cautious about Big Data?

Join Jane Griffin as she shares how organizations can corral on big data to enable business decisions and bring agility to their business intelligence.

Speaker: Jane Griffin, Executive Advisor, Deloitte Canada


9:20-10:10am • Room: 713

Keynote
The Challenge of Data (Big or Small) in Predictive Analytics

Big Data is the latest buzzword in business circles today. How do we deal with exploding volumes of data? The world of predictive data analytics and data mining has always dealt with big data but the digital world and social media have increased this to a new scale. Are there disciplines and practices that deal with analytics of big data? More importantly, how differently do practitioners need to evolve their practices to reflect the new reality?

This session will look at how practitioners integrate the Big Data practices of the "old world" vs. the "new world." For example, what are the types of "Big Data" practices that have been consistently applied in predictive analytics projects over the last 20 years and which are currently still reliable today? Yet, practitioners need to also ware of new practices and approaches that attempt to meet this increasing demand for more time-sensitive solutions particularly within the social media space. Finally, this session will look at how practitioners should draw on their knowledge of the old and the new data environments in order to identify what makes sense in delivering solutions within this new frenetic environment.

Speaker: Richard Boire, Founding Partner, Boire Filler Group

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10:10-10:40am • Room: Foyer

Exhibits & Morning Coffee Break


SAS 10:40-10:50am • Room: 713

Gold Sponsor Presentation
Analytics & Crunching the Future

This 7-8 minute presentation will provide a non-industry specific overview on where analytics has come from, up to present day, with a vision to the future. The presentation will touch on the impact and implications that Big Data has had on the Analytic community and the resulting technological response from vendors in the form of High Performance Analytics and data visualization

Speaker: Stuart Rose, Global Insurance Marketing Manager, SAS Institute


10:50-11:35am • Room: 711

Track 1: Churn Modeling
Case Study: Data Insight Group
Divide and Conquer: Enhancing Predictions through Segmentation

This session explores how segmentation and modeling can be integrated to achieve better business results. At the same time, the session explores when it does and does not make sense to build a multi-model approach within multiple segments where reduction of churn is the ultimate business objective.

Speaker: Emma Warrillow, President, Data Insight Group

10:50-11:35am • Room: 713

Track 2: Financial Services
Case Study: Scotiabank
Mortgage Liquidation Model Building and Application

The purpose of development of a mortgage liquidation model is to enable Group Treasury and Asset Liability Management to reduce cash flow uncertainty and improve budgeting and hedge effectiveness. A multinomial logistic regression model was built to predict two mortgage events: full payment and early renewal. The model was vetted by the validation team, and applied to cash flow analysis and gap reporting.

Speakers: Jane Zhong, Senior Manager of Predictive Analytics, Scotiabank
Wenlei Shi, Manager, Statistical Analysis, Scotiabank

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11:40-12:25pm • Room: 711

Track 1: Spam Detection
Case Study: MailChimp.com
Monkeys & Math: How MailChimp Catches Bad Guys

Hear from MailChimp's Chief Scientist John Foreman as he dishes on dirty data and demonstrates the latest in MailChimp's anti-abuse artificial intelligence. MailChimp sends 3 billion emails a month for their millions of users, and they can't afford to let a drop of spam go out. Learn how the company is using cutting edge NoSQL solutions and predictive models to leave the bad guys out in the cold.

Speaker: John Foreman, Chief Scientist, MailChimp.com

11:40-12:25pm • Room: 713

Thought Leadership
My Five Predictive Analytics Pet Peeves

Predictive Analytics (PA) has become increasingly mature as a technical discipline over the past decade in part because it stands on the shoulders of the related disciplines of data mining and machine learning. However, there are recurring themes that permeate discussion boards and conferences that have become my personal pet peeves. This talk examines five of them and why they matter to practitioners, including why we must have humility in how far data science and algorithms can take us, and the value of business objectives, measuring "success," and measuring "significance."

Speaker: Dean Abbott, President, Abbott Analytics, Inc.

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12:25-1:30pm • Room: Foyer

Lunch / Exhibits


1:30-2:15pm • Room: 713

Special Plenary Session
Becoming an Ace with a Robot as your Wingman!

Humans and computers have strengths that are more complementary than alike – to the point where a sophisticated algorithm may be the best "2nd person" to put on a complex task. Yet, our and computer analytic weaknesses are surprisingly severe. To explore how to improve the man/machine partnership, we compare and contrast natural and artificial intelligence, with special attention to the growing realization of how challenging it is to think truly rationally.

Speaker: Dr. John Elder, CEO and Founder, Elder Research, Inc.

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2:15-2:30pm • Room: 713

Lightning Round of 2-Minute Sponsor Presentations
SAS    Deloitte    Managed Analytic Services    getClarity        verint


2:35–3:20pm • Room: 711

Track 1: Military
Case Study: RITRE
The New Intelligence Tradecraft: Case Studies of Activity Based Intelligence Enabled by the Application of Predictive Analytics Tools on Big Data - a Discussion of Experience and Future Potential

Military Intelligence has been one of the leading areas in the application of analytical processes to predict events. Previously, the analyst would assess and compare bits and pieces of raw information, and synthesize findings into an intelligence product to reflect enemy capabilities and vulnerability. In an era of rapidly multiplying data sources and data volumes, the pace of innovation has expanded dramatically and outcomes are optimized when decision makers experience a shared situational awareness which is enriched when we are able to leapfrog into the world of predictive analytics by exposing and aligning data streams in near real time.

Speaker: Joseph D. Fargnoli, Fellow, RITRE Corporation

2:35–3:20pm • Room: 713

Track 2: Brand Analytics
Case Study: Dell
The Illusive Brand: How to Measure Brand and the Communications Focused On It

Measuring a brand health is very difficult and can be convoluted. Often, if you have multiple metrics such as NPS or survey results, they will not align on how your brand health is changing. Helping business leaders understand how they can impact brand health is even more difficult. Natalie will present ideas on how to model out marketing's impacts on the brand, measuring the long-term impacts of an overriding campaign, and how to handle differing trends from various brand health metrics. In addition, we will discuss how to explain these models and their errors to decision makers.

Speaker: Natalie Kortum, Marketing Decision Scientist, Dell

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3:20-3:50pm • Room: Foyer

Exhibits & Afternoon Break

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3:50-4:35pm • Room: 713

Track 1: Brand Analytics
Case Study: a Fortune 500 Company
Using Attitudinal Behaviour to Determine Media Spend

With one of their clients being a key manufacturer of diapers, this organization demonstrated how data could be used to determine their key areas of media spend. In targeting their efforts to Moms, the organization redefined their target segment as the Ultra Value Conscious Mom. Data was then used to determine the ideal media that contained more consumers who fit the Ultra Value Conscious Mom.

Speaker: Shel Smith, Senior Principal, Twenty Ten

3:50-4:35pm • Room: 711

Track 2: Insurance
Case Study: Broadspire
To Sue or Not to Sue: Predicting Litigation Risk

Litigation is a major cost factor in handling casualty claims. Follow the development and testing of a "double barreled" litigation prediction application for our claims system and our parallel e-Triage system, which provides a richer data environment for certain types of insurance claims. This is a major enhancement of a robust predictive system now in use for over six years and an expansion of predictive know-how to control claim costs. See how we apply our continuous improvement philosophy to making predictive analytics a core competency inside an industry leading claims service.

Speakers: Gary Anderberg, Practice Leader, Analytics and Outcomes, Broadspire
Bangalore Gunashakar, Senior Technical Consultant, Broadspire
Sergo Grigalashvili, VP Architecture, Analytics, GSR, Crawford & Company

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4:40-5:30pm • Room: 713

Panel Discussion
Predictive Analytics in Insurance Risk

Moderator: Stuart Rose, Global Insurance Marketing Manager, SAS Institute

At this session, three Canadian seasoned insurance practitioners give their view-point from an actuarial perspective, advanced analytics perspective and business perspective on the importance of predictive analytics in insurance risk. The discussion will focus on the data challenges, underwriting challenges, on the regulatory challenges in using these tools for pricing, as well as data challenges in building predictive analytics solutions and challenges related to developing effective underwriting strategies

Panelists: Jamie McDougall, Vice President, Personal Insurance Solutions
Hashmat Rohian, AVP Research & Development, Aviva Canada
Colin Smith, Vice President of Operations, Opta Information Intelligence

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5:30-7:00pm • Room: Foyer

Reception / Exhibits

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Conference Day 2: Thursday, March 21, 2013

8:00-9:00am • Room: Foyer

Registration & Networking Breakfast


9:00-9:05am • Room: 713

Conference Chair Welcome Remarks

Speaker: Richard Boire, Conference Chair, Predictive Analytics World Toronto


9:05-9:55am • Room: 713

Keynote
Enabling Data Driven Marketing in a Digital and Social World

The world of marketing, technology and data management has never been so complex and the need to deepen the integration across these functions is accelerating at an unprecedented rate. But do new forms of data, both structured and unstructured, create an opportunity to improve our decision science, develop more meaningful relationships with Customers and enhance shareholder returns? Is the explosion of data and multiple digital devices for each individual an opportunity or a risk for the models that we have and for Marketers of the future?

This session will focus on digital marketing and examine how American Express is exploring new approaches to better understand and answer the above questions. It will also illustrate how American Express is analyzing multi-channel marketing attribution and articulate how American Express is refining internal processes and platforms to become best in class digital Marketers. Lastly, it will look to illustrate new opportunities to integrate data into ongoing processes and highlight the importance of leveraging traditional and non-traditional approaches in both test design and the collection of Consumer insights.

Speaker: Brett Mooney,Vice President, Consumer Acquisition and Management, American Express

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9:55-10:50am • Room: Foyer

Exhibits & Morning Coffee Break


10:50-11:35am • Room: 711

Track 1: Recruitment Analytics
Case Study: Talent Analytics
Using Analytics to Build Your Analytics Bench: Announcing 2012 Analytics Professionals Study Results

Many innovative businesses and IT organizations appreciate the competitive advantage analytics capabilities can provide and have ambitions to reach increasing levels of analytics maturity. However, the well-documented shortage of analytic talent leaves many firms without a strong analytic talent bench and little knowledge about how and where to find analytics professionals needed to get there. In this presentation, Greta Roberts will discuss results from a major 2012 Study of Analytics Professionals that crosses industries, experience and skills. Practical insights shared include key best practices, trends and correlations that lend unexpected insight into building a strong and scalable analytic talent bench.

Speaker: Greta Roberts, Faculty Member, International Institute for Analytics


10:50-11:35am • Room: 713

Track 2: Retail
Case Study: MakePlain/Boire Filler Group
The Exploding World of Data: The Retail Impact

With the ever-abundance of data in the retail world, how do we make sense of it. With hundreds of millions of transactions being the typical norm, retailers need to be nimble to use this information effectively. From this case study, we learn how a certain analytical approach complemented with certain tools quickly enabled this organization to make effective decisions.

Speakers: Larry Filler, Partner, Boire Filler Group
Gary Sarrenvirta, President, MakePlain Corp.

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11:40am–12:25pm • Room: 713

Track 1: Big Data Analytics
Case Study: Precog
The Productization of Predictive Analytics

Many companies are using the predictive analytics to forecast and optimize internal business processes. However, for companies possessing large amounts of proprietary data, there is another way to leverage predictive analytics: leveraging predictive models to create new data products and incorporate data-driven features inside existing products. In this presentation, data productization expert John A. De Goes provides an introduction to productizing predictive analytics, including case studies of companies finding innovative ways to monetize their data assets via productization of predictive models. John also discusses tools and technologies that are typically required to perform productization in today's big data world.

Speaker: John De Goes, CEO and CTO, Precog


11:40am–12:25pm • Room: 711

Track 2: Net Lift
Case Study: Pitney Bowes
Uplift Modeling in Theory & Practice

During this session, we'll review the current state of the art in "uplift modeling" - the practice of modeling the change in behavior that results directly from a specific treatment such as a marketing intervention. We will discuss approaches to variable selection, model construction, quality metrics and post-campaign success measurements, all of which require changes from traditional modeling practices. We'll illustrate with practical examples from demand-stimulation and customer retention applications, and highlight potential pitfalls to avoid.

Speaker: Dr. Patrick Surry, Global Solution Owner for Customer Analytics, Pitney Bowes

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12:25-1:40pm • Room: Foyer

Lunch


1:40-2:25pm Room: 713

Plenary Session
Case Study: Sport Analytics Institute
Succeeding with Analytics in Professional Hockey - Now and Into the Future

This talk will cover a range of topics related to successfully using analytics in NHL organizations. Using examples from his experience, Dan MacKinnon, Director of Player Personnel of the Pittsburgh Penguins, will discuss the changing culture and evolution of analytics in hockey and how he incorporates data and analytics into his day-to-day role of evaluating future talent and managing existing player personnel. Mike Boyle, Co-founder of the Sports Analytics Institute and Assistant Professor of Information Systems at the University of Utah, will discuss how best practices for achieving success with analytics in other industries can be similarly applied within NHL organizations. Kevin Mongeon, also Co-founder of the Sports Analytics Institute and Assistant Professor of Economics at the University of New Haven, will discuss the difference between analytics in hockey compared to other sports and how appropriate use of the data is key to achieving accurate results. Together the group will discuss the future of data and analytics within NHL organizations and into the broader elite hockey system.

Speakers: Kevin Mongeon, Co-Founder, Sports Analytics Institute
Mike Boyle, Co-Founder, Sports Analytics Institute
Dan MacKinnon, Director of Player Personnel, Pittsburgh Penguins

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2:30-3:15pm Room: 713

Panel Discussion
What is Big Data Analytics: A Canadian Perspective

Moderator: Richard Boire, Conference Chair, Predictive Analytics World

During this session, three of the very most seasoned Canadian practitioners give their perspective on Big Data and ultimately data itself. The discussion's focus on data will yield insights on how practitioners need to think about analytics in this new data paradigm.

Panelists: Dean Abbott, President, Abbott Analytics, Inc.
Rupen Seoni, Vice President, Practice Leader, Environics Analytics
Paul Tyndall, Advanced Analytics Team Lead, RBC

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3:15-3:50pm Room: Foyer

Exhibits & Afternoon Break

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3:50–4:35pm Room: 713

Track 1: Data Visualization
Unlocking the Voice of Your Customer Through Text Analytics

Key topics I'll cover include:

  • The potential new sources of client data which text analytics allows you to leverage
  • What types of data elements are available and how to use them
  • Opportunities to integrate Voice of the Client data with traditional data to enhance your predictive analytics
  • Potential challenges with Text Analytics to consider
Speaker: Paul Tyndall, Advanced Analytics Team Lead, RBC

3:50–4:35pm Room: 711

Track 2: Recruitment Analytics
Case Study: Monster Worldwide
Win With Advanced Analytics

Monster was the pioneer in the online recruitment industry. To maintain its competitive advantage, it has taken the data-driven road using research, business intelligence and predictive analytics and text analytics. Join this session to hear how Monster went from good to great using business analytics to support its overall decision-making process across all regions. Jean-Paul Isson will provide highlights from his new book, "Major Steps to Win with Analytics with the Big Data." He will also discuss Monster's success with increasing customer retention, market share and customer profitability, while managing competition from paid sites, free sites and social networks.

Speaker: Jean-Paul Isson, Global VP Predictive Analytics & BI, Monster Worldwide

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4:40-5:30pm Room: 711

Track 1: Churn Modeling
Case Study: Paychex
Customer Retention: Pulling the Needle from the Haystack

In these economic times, it is critical for businesses to have a stronghold on client retention, with businesses excelling in this arena better positioned for long-term success. To optimize the value of retention efforts, it's essential to understand which clients are the best fit for retention campaigns. In this session, we will review how Paychex leveraged two existing models, Paychex Attrition Model and a custom-built Lifetime Value Model, to create a Retention Tracking System (RTS). Since being deployed across the entire branch network, the RTS has become an invaluable resource as offices nation-wide strive to meet, and exceed, retention goals.

Speakers: Erika McBride, Manager of Modeling & Risk Review, Paychex, Inc.
Tom Kern, Risk Modeling Analyst, Paychex, Inc.

4:40-5:30pm Room: 713

Track 2: Financial Services
Case Study: TD Bank
Marketing Predictive Models (Response, Survival and Premium Models) for Credit Card Insurance

This session will present marketing predictive models that are based on the customer willingness to buy credit card insurance and could help marketers to identify the life expectancy and the expected lifetime premium. This case study improves decision-making processes, resulting in more profitable and efficient operations.

Speaker: Dr. Hasan Mytkolli, Lead - Statistical Modeling, Forecasting and Reporting, TD Bank Group Canada
Dr. Dragos Calitoiu, Senior Modeler, TD Bank Group Canada

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